SearcharxivSearch

arXiv subjects

Filip Rezabek

Publications and source records attributed to Filip Rezabek.

11 recordsLinked to original sources

Space Fabric: A Satellite-Enhanced Trusted Execution Architecture

The emergence of decentralized satellite networks creates a pressing need for trust architectures that operate without physical access to hardware, without pre-provisioned vendor secrets, and without dependence on a single manufacturer's attestation service. Terrestrial TEEs are insufficient: hardware-based designs are susceptible to physical attacks, and most platforms root their attestation chains in secrets provisioned during manufacturing, creating a pre-launch trust window and single-vendor dependency that cannot be independently audited. We present Space Fabric, an architecture that provides the missing trust foundation for orbital computing by relocating the trusted computing stack to satellite infrastructure, exploiting post-launch physical inaccessibility as a tamper barrier unattainable by terrestrial deployments. Our Satellite Execution Assurance Protocol binds workload execution to a specific satellite via a Byzantine-tolerant endorsement quorum of distributed ground stations, certifying not only \emph{what} executes inside the TEE but also \emph{where}. All cryptographic secrets are generated within co-located secure elements after launch, with no signing keys accessible on Earth at any point. To reduce single-vendor dependence, Space Fabric distributes its trust anchor across two independent secure elements, an NXP SE050 and a TROPIC01, both of which must co-sign attestation evidence. We implement Space Fabric on a USB Armory Mk II with ARM TrustZone, verify attestation end-to-end using Veraison, and provide a security analysis with satisfaction arguments and impossibility bounds under a strong adaptive adversary.

cs.CR

Proof of Cloud: Data Center Execution Assurance for Confidential VMs

Confidential Virtual Machines (CVMs) protect data in use by running workloads within hardware-enforced Trusted Execution Environments (TEEs). However, existing CVM attestation mechanisms only certify what code is running, not where it is running. Commercial TEEs mitigate passive physical attacks through memory encryption but explicitly exclude active hardware tampering (memory interposers, physical side channels, ...). Yet current attestations provide no cryptographic evidence that a CVM executes on hardware residing within a trusted data center where such attacks would not take place. This gap enables proxy attacks in which valid attestations are combined across machines to falsely attest trusted execution. To bridge this gap, we introduce Data Center Execution Assurance (DCEA), a design that generates a cryptographic Proof of Cloud by binding CVM attestation to platform-level Trusted Platform Module (TPM) evidence. DCEA combines two independent roots of trust. First, the TEE manufacturer, and second, the infrastructure provider, by cross-linking runtime TEE measurements with the vTPM-measured boot CVM state. This binding ensures that CVM execution, vTPM quotes, and platform provenance all originate from the same physical chassis. We formalize the environment's provenance and show that DCEA prevents advanced relay attacks, including a novel mix-and-match proxy attack. Using the AGATE framework in the Universal Composability model, we prove that DCEA emulates an ideal location-aware TEE even under a malicious host software stack. We implement DCEA on Google Cloud bare-metal Intel TDX instances using Intel TXT and evaluate its performance, demonstrating practical overheads and deployability. DCEA refines the CVM threat model and enables verifiable execution-location guarantees for privacy-sensitive workloads.

cs.CR

Threshold Signatures for Central Bank Digital Currencies

Digital signatures are crucial for securing Central Bank Digital Currencies (CBDCs) transactions. Like most forms of digital currencies, CBDC solutions rely on signatures for transaction authenticity and integrity, leading to major issues in the case of private key compromise. Our work explores threshold signature schemes (TSSs) in the context of CBDCs. TSSs allow distributed key management and signing, reducing the risk of a compromised key. We analyze CBDC-specific requirements, considering the applicability of TSSs, and use Filia CBDC solution as a base for a detailed evaluation. As most of the current solutions rely on ECDSA for compatibility, we focus on ECDSA-based TSSs and their supporting libraries. Our performance evaluation measured the computational and communication complexity across key processes, as well as the throughput and latency of end-to-end transactions. The results confirm that TSS can enhance the security of CBDC implementations while maintaining acceptable performance for real-world deployments.

cs.CR

Narrowing the Gap between TEEs Threat Model and Deployment Strategies

Confidential Virtual Machines (CVMs) provide isolation guarantees for data in use, but their threat model does not include physical level protection and side-channel attacks. Therefore, current deployments rely on trusted cloud providers to host the CVMs' underlying infrastructure. However, TEE attestations do not provide information about the operator hosting a CVM. Without knowing whether a Trusted Execution Environment (TEE) runs within a provider's infrastructure, a user cannot accurately assess the risks of physical attacks. We observe a misalignment in the threat model where the workloads are protected against other tenants but do not offer end-to-end security assurances to external users without relying on cloud providers. The attestation should be extended to bind the CVM with the provider. A possible solution can rely on the Protected Platform Identifier (PPID), a unique CPU identifier. However, the implementation details of various TEE manufacturers, attestation flows, and providers vary. This makes verification of attestations, ease of migration, and building applications without relying on a trusted party challenging, highlighting a key limitation that must be addressed for the adoption of CVMs. We discuss two points focusing on hardening and extensions of TEEs' attestation.

cs.CR

Cross-Chain Arbitrage: The Next Frontier of MEV in Decentralized Finance

Decentralized finance (DeFi) markets spread across Layer-1 (L1) and Layer-2 (L2) blockchains rely on arbitrage to keep prices aligned. Today most price gaps are closed against centralized exchanges (CEXes), whose deep liquidity and fast execution make them the primary venue for price discovery. As trading volume migrates on-chain, cross-chain arbitrage between decentralized exchanges (DEXes) will become the canonical mechanism for price alignment. Yet, despite its importance to DeFi-and the on-chain transparency making real activity tractable in a way CEX-to-DEX arbitrage is not-existing research remains confined to conceptual overviews and hypothetical opportunity analyses. We study cross-chain arbitrage with a profit-cost model and a year-long measurement. The model shows that opportunity frequency, bridging time, and token depreciation determine whether inventory- or bridge-based execution is more profitable. Empirically, we analyze one year of transactions (September 2023 - August 2024) across nine blockchains and identify 242,535 executed arbitrages totaling 868.64 million USD volume. Activity clusters on Ethereum-centric L1-L2 pairs, grows 5.5x over the study period, and surges-higher volume, more trades, lower fees-after the Dencun upgrade (March 13, 2024). Most trades use pre-positioned inventory (66.96%) and settle in 9s, whereas bridge-based arbitrages take 242s, underscoring the latency cost of today's bridges. Market concentration is high: the five largest addresses execute more than half of all trades, and one alone captures almost 40% of daily volume post-Dencun. We conclude that cross-chain arbitrage fosters vertical integration, centralizing sequencing infrastructure and economic power and thereby exacerbating censorship, liveness, and finality risks; decentralizing block building and lowering entry barriers are critical to countering these threats.

cs.CR

Playing the MEV Game on a First-Come-First-Served Blockchain

Maximal Extractable Value (MEV) searching has gained prominence on the Ethereum blockchain since the surge in Decentralized Finance activities. In Ethereum, MEV extraction primarily hinges on fee payments to block proposers. However, in First-Come-First-Served (FCFS) blockchain networks, the focus shifts to latency optimizations, akin to High-Frequency Trading in Traditional Finance. This paper illustrates the dynamics of the MEV extraction game in an FCFS network, specifically Algorand. We introduce an arbitrage detection algorithm tailored to the unique time constraints of FCFS networks and assess its effectiveness. Additionally, our experiments investigate potential optimizations in Algorand's network layer to secure optimal execution positions. Our analysis reveals that while the states of relevant trading pools are updated approximately every six blocks on median, pursuing MEV at the block state level is not viable on Algorand, as arbitrage opportunities are typically executed within the blocks they appear. Our algorithm's performance under varying time constraints underscores the importance of timing in arbitrage discovery. Furthermore, our network-level experiments identify critical transaction prioritization strategies for Algorand's FCFS network. Key among these is reducing latency in connections with relays that are well-connected to high-staked proposers.

cs.CR

Real-Time Performance of OPC UA

OPC UA is an industry-standard machine-to-machine communication protocol in the Industrial Internet of Things. It relies on time-sensitive networking to meet the real-time requirements of various applications. Time-sensitive networking is implemented through various queueing disciplines (qdiscs), including Time Aware Priority, Multiqueue Priority, Earliest TxTime First, and Credit-Based Shaper. Despite their significance, prior studies on these qdiscs have been limited to a few. They have often been confined to point-to-point network topologies using proprietary software or specialized hardware. This study builds upon existing research by evaluating all these qdiscs in point-to-point and bridged topologies using open-source software on commercial off-the-shelf hardware. We first identify the optimal configuration for each qdisc and then compare their jitter, latency, and reliability through experiments. Our results show that open-source OPC UA on commercial off-the-shelf hardware can effectively meet the stringent real-time requirements of many industrial applications and provide a foundation for future research and practical deployments.

cs.NI

Multilayer Environment and Toolchain for Holistic NetwOrk Design and Analysis

The recent developments and research in distributed ledger technologies and blockchain have contributed to the increasing adoption of distributed systems. To collect relevant insights into systems' behavior, we observe many evaluation frameworks focusing mainly on the system under test throughput. However, these frameworks often need more comprehensiveness and generality, particularly in adopting a distributed applications' cross-layer approach. This work analyses in detail the requirements for distributed systems assessment. We summarize these findings into a structured methodology and experimentation framework called METHODA. Our approach emphasizes setting up and assessing a broader spectrum of distributed systems and addresses a notable research gap. We showcase the effectiveness of the framework by evaluating four distinct systems and their interaction, leveraging a diverse set of eight carefully selected metrics and 12 essential parameters. Through experimentation and analysis we demonstrate the framework's capabilities to provide valuable insights across various use cases. For instance, we identify that a combination of Trusted Execution Environments with threshold signature scheme FROST introduces minimal overhead on the performance with average latency around \SI{40}{\ms}. We showcase an emulation of realistic systems behavior, e.g., Maximal Extractable Value is possible and could be used to further model such dynamics. The METHODA framework enables a deeper understanding of distributed systems and is a powerful tool for researchers and practitioners navigating the complex landscape of modern computing infrastructures.

cs.DC

EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application

While current research and development of autonomous driving primarily focuses on developing new features and algorithms, the transfer from isolated software components into an entire software stack has been covered sparsely. Besides that, due to the complexity of autonomous software stacks and public road traffic, the optimal validation of entire stacks is an open research problem. Our paper targets these two aspects. We present our autonomous research vehicle EDGAR and its digital twin, a detailed virtual duplication of the vehicle. While the vehicle's setup is closely related to the state of the art, its virtual duplication is a valuable contribution as it is crucial for a consistent validation process from simulation to real-world tests. In addition, different development teams can work with the same model, making integration and testing of the software stacks much easier, significantly accelerating the development process. The real and virtual vehicles are embedded in a comprehensive development environment, which is also introduced. All parameters of the digital twin are provided open-source at https://github.com/TUMFTM/edgar_digital_twin.

cs.RO

A Study of MEV Extraction Techniques on a First-Come-First-Served Blockchain

Maximal Extractable Value (MEV) has become a significant incentive on blockchain networks, referring to the value captured through the manipulation of transaction execution order and strategic issuance of profit-generation transactions. We argue that transaction ordering techniques used for MEV extraction in blockchains where fees can influence the execution order do not directly apply to blockchains where the order is determined based on transactions' arrival times. Such blockchains' First-Come-First-Served (FCFS) nature can yield different optimization strategies for entities seeking MEV, known as searchers, requiring further study. This paper explores the applicability of MEV extraction techniques observed on Ethereum, a fee-based blockchain, to Algorand, an FCFS blockchain. Our results show the prevalence of arbitrage MEV getting extracted through backruns on pending transactions in the network, uniformly distributed to block positions. However, on-chain data do not reveal latency optimizations between specific MEV searchers and Algorand block proposers. We also study network clogging attacks and argue how searchers can exploit them as a viable ordering technique for MEV extraction in FCFS networks.

cs.CR

On the Requirements for Serious Games geared towards Software Developers in the Industry

Teaching industry staff on cybersecurity issues is a fundamental activity that must be undertaken in order to guarantee the delivery of successful and robust products to market. Much research attention has been devoted to this topic over the last years. However, the research which has been done has not focused on developing secure code in industrial environments. In this paper we take a look at the constraints and requirements for delivering a training, by means of cybersecurity challenges, that covers secure coding topics from an industry perspective. Using requirements engineering, we aim at understanding the design requirements for such challenges. Along the way, we give details on our experience of delivering cybersecurity challenges in an industrial setting and show the outcome and lessons learned. The proposed requirements for cybersecurity challenges geared towards software developers in an industrial environment are based on systematic literature review, interviews with security experts from the industry and semi-structured evaluation of participant feedback.

cs.SE